Sihan Zhou
Papers
1
Total Citations
5
H-Index
1
About
Sihan Zhou is a rising researcher in the field of intelligent prosthetics and human-machine interaction, with a focus on advancing assistive technology through deep learning and embedded systems. Their most notable contribution is the development of a wireless, sEMG-controlled prosthetic hand that integrates a novel, ultra-compact CNN-Transformer model—just 169 kB in size—capable of classifying 21 distinct hand gestures from surface electromyography signals. This work, published in 2023 and already garnering 5 citations, represents a significant step toward more natural, responsive, and affordable prosthetic control by combining real-time force feedback with a lightweight neural architecture. Zhou’s research addresses critical challenges in prosthetic usability, including gesture recognition accuracy and computational efficiency for embedded devices. Their achievements highlight a commitment to bridging the gap between advanced AI models and practical, wearable biomedical systems. As an emerging scholar, Sihan Zhou’s work holds promise for transforming the lives of amputees and individuals with limb differences, making intuitive, feedback-rich prosthetic hands more accessible.
Research Focus
Key Achievements
Top Papers
- 1